Sentences with phrase «linear age model»

If you consider the existing uncertainties in dating and simple linear age model, we could get some strong leads.

Not exact matches

We used multiple regression to estimate the differences in total cost between the settings for birth and to adjust for potential confounders, including maternal age, parity, ethnicity, understanding of English, marital status, BMI, index of multiple deprivation score, parity, and gestational age at birth, which could each be associated with planned place of birth and with adverse outcomes.12 For the generalised linear model on costs, we selected a γ distribution and identity link function in preference to alternative distributional forms and link functions on the basis of its low Akaike's information criterion (AIC) statistic.

Decline in cognitive test scores over 10 years (% change = change / range of text × 100) as function of baseline age cohort in men and women, estimated from linear mixed models.

To test for differences in growth rates between genotypes, we fit the data using linear models regressing larval weight against age and tested for differences in the interaction term between larval age and genotype using ANCOVA and post hoc comparisons of the slopes of fitted lines using lstrends (HH and lsmeans packages).

For studies that reported incidence in each age category, we fitted log - linear model that contained incidence (dependent variable) and consumption (independent variable) with age as a covariate (median age in each age category), and we estimated the relative risk by using an interaction term between age and consumption.

The linear regression models were adjusted for age and other confounders.

In a linear mixed model adjusted for age, sex, education, participation in cognitive activities, physical activities, smoking, and seafood and alcohol consumption, consumption of green leafy vegetables was associated with slower cognitive decline; the decline rate for those in the highest quintile of intake (median 1.3 servings / d) was slower by β = 0.05 standardized units (p = 0.0001) or the equivalent of being 11 years younger in age.

Figure 2 shows results from estimating a linear probability model predicting the probability that a child in the school - aged (5 - 17) subpopulation of the NSCH currently has an IEP.

The effects of age and sperm state (fresh vs chilled) on the above sperm endpoints were determined using a linear mixed effects model.

We built a generalized estimating equation (GEE) general linear model (GLM) with outcome as the dependent variable; time in the nursing box, licking / grooming per puppy, vertical nursing per puppy, and ventral nursing per puppy were entered as predictors with breed, maternal parity, sex of puppy, and age at return entered as covariates.

The effect of maternal care and age of separation (from the mother) on TC was also evaluated using a generalized linear model with a binomial distribution.

There is a sizeable and significant role of education in predicting knowledge on the index even when controlling for gender, age, and race and ethnicity in a linear regression model.

Inset figure shows the relationship between δ13C and age (in years) using a linear mixed effects model for each of the 3 shell groupings.

For all plots combined, tree growth rates, calculated as relative growth in total basal area, were observed to decline significantly, regardless of ages [Fig. 2C; P < 0.001, linear mixed model (LMM)-RSB-.

Because of the linear term, you might expect the model to match the observations back to the Little Ice Age (LIA) and then rapidly diverge from observations.

I have tried a simple anova linear model using the lm procedure in R taking the logs of the tree ring widths and using three factors: tree, age and year (a total of about 2874 parameters) and the program bailed out with the complaint» Reached total allocation of 957Mb: see help (memory.size)».

In fact, you can get a very good fit with actual temperature by modeling them as three functions: A 63 - year sine wave, a 0.4 C per century long - term linear trend (e.g. recovery from the little ice age) and a new trend starting in 1945 of an additional 0.35 C, possibly from manmade CO2.

Paradigms anchored too firmly to specific media, sources, or linear models are becoming ineffective compasses for navigating the legal research process in the information age.

We applied generalised linear mixed models via PROC GLIMMIX to estimate the effects of different transitional patterns of exercise on depressive symptoms with HLDS as the event, after adjusting for the previous CESD score, age, gender, level of education, marital status, smoking, physical function, emotional support, social participation, self - rated health, economic satisfaction, employment and 10 chronic conditions.

Univariate generalized linear models were used to determine the estimated marginal means of the PedsQL scales and subscales adjusting for the child's age, sex, maternal education, and disadvantage index as covariates.

Trends in rates of child diagnoses by mother's response level in children with a baseline diagnosis and in rates of incidence or relapse in children without a baseline diagnoses were examined separately using the Cochran - Armitage test for trend.29 Low event rates precluded fitting regression models adjusting for potential confounders, such as age and sex of child, using generalized linear models with an identity - link function, to estimate parameters for adjusted trends.

General linear models testing for effects of sex and age (6 - month bands) indicated no age effect for BITSEA / P (Table I).

Hierarchical linear modeling analyses of the NEO-PI-R scales in the Baltimore Longitudinal Study of Aging

Given poor robustness of t - tests with very different group sizes, we used t ′ assuming lack of homogeneity of variance; control analysis was tested with general linear model (GLM) controlling for age, depressive symptoms, and self - rated health (df = 1).

1Maternal reports of partner's alcohol consumption; 2Univariable linear regression models; 3Models adjusted for maternal age at delivery, parity, social economic position, maternal education, maternal smoking during first trimester in pregnancy, housing tenure, income, and maternal depressive symptoms at 32 weeks gestation.

After combining the two samples, we then extended the ESEM model to test measurement invariance across several group configurations (gender, age, and gender × age), evaluated the potential linear and quadratic effects of age through MIMIC models, and then combined the two methods by adding the MIMIC age effects to the gender × age invariance model.

We used linear mixed regression models with random intercept and slope (random effects models) to examine the extent to which the predictor variables considered influenced changes in continuous CBCL total, internalising, and externalising T scores from ages 2 to 14.

Simple effects of callous - unemotional traits were tested in a general linear model (GLM) with age, IQ, ADHD symptoms, and PDS and PESQ scores added as covariates of no interest.

We examined differences in diary scales (secure, avoidant, resistant, and coherence) as they related to age at placement and foster parent attachment, using hierarchical linear modeling and analyses of variance.

The effects of age, IQ, ADHD symptoms, pubertal stage and substance abuse were removed by fitting a linear model (with no interactions) and the residuals of the model were plotted against callous - unemotional traits